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Visual field maps in human cortex.
Open accessAbstract
Much of the visual cortex is organized into visual field maps: nearby neurons have receptive fields at nearby locations in the image. Mammalian species generally have multiple visual field maps with each species having similar, but not identical, maps. The introduction of functional magnetic resonance imaging made it possible to identify visual field maps in human cortex, including several near (1) medial occipital (V1,V2,V3), (2) lateral occipital (LO-1,LO-2, hMT+), (3) ventral occipital (hV4, VO-1, VO-2), (4) dorsal occipital (V3A, V3B), and (5) posterior parietal cortex (IPS-0 to IPS-4). Evidence is accumulating for additional maps, including some in the frontal lobe. Cortical maps are arranged into clusters in which several maps have parallel eccentricity representations, while the angular representations within a cluster alternate in visual field sign. Visual field maps have been linked to functional and perceptual properties of the visual system at various spatial scales, ranging from the level of individual maps to map clusters to dorsal-ventral streams. We survey recent measurements of human visual field maps, describe hypotheses about the function and relationships between maps, and consider methods to improve map measurements and characterize the response properties of neurons comprising these maps.
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“It is likely that the developmental changes we document in the LOTS reflect increased sensitivity to visual inputs delivered through neighboring ventral visual areas such as hV4, VO1, and VO2 (Ben-Shachar et al., 2007; Wandell, Dumoulin, & Brewer, 2007).”
From The Development of Cortical Sensitivity to Visual Word Forms (2011) · cites this paper as Wandell et al., 2007
In the citing paper
“Hence, the circuits here provide no explanation for observed cortical maps [70],[71].”
From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [70]
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“Much of the visual system is organized into visual field maps ( Wandell et al., 2007).”
BackgroundYashar, A., & Carrasco, M. (2024) · Psychonomic Bulletin & Review · doi:10.3758/s13423-024-02580-7 · Cited by 3
Biases in Volumetric Versus Surface Analyses in Population Receptive Field Mapping
Linhardt, D., Woletz, M., Paz‐Alonso, P. M., Windischberger, C., & Lerma‐Usabiaga, G. (2025) · Human Brain Mapping · doi:10.1002/hbm.70140 · Cited by 4
Ferreira, S., Pereira, A. C., Quendera, B., Reis, A., Silva, E. D., & Castelo-Branco, M. S. (2019) · Neural Plasticity · doi:10.1155/2019/8136354 · Cited by 4
“Polar angle and eccentricity stimuli were employed to delineate the cortical visual areas (V1, V2, and V3) using the traveling-wave approach from the standard phase-encoded retinotopic mapping [27].”
Bhat, A., Kurzawski, J. W., Anobile, G., Tinelli, F., Biagi, L., & Morrone, M. C. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23031055 · Cited by 3
Functional Imaging of the Human Visual System
Orban, G. A., & Ferri, S. (2016) · Neuromethods · doi:10.1007/978-1-4939-5611-1_18 · Cited by 3
DiNuzzo, M., Mascali, D., Moraschi, M., Bussu, G., Maraviglia, B., Mangia, S., & Giove, F. (2017) · Frontiers in Physics · doi:10.3389/fphy.2017.00007 · Cited by 3
“This approach is unsuited to exactly identify the cortical area whose neuronal receptive field matches the stimulus location [25], however it has the advantage of relying on the data themselves, not requiring further acquisitions spatially coregistered with the main experiment data, and proved successful in the identi…”
MethodUsing Vision to Study Poststroke Recovery and Test Hypotheses About Neurorehabilitation
Busza, A. C., Schneider, C., Williams, Z. R., Mahon, B. Z., & Sahin, B. (2019) · Neurorehabilitation and neural repair · doi:10.1177/1545968319827569 · Cited by 3
“The early visual cortex (V1) in particular is known to have a highly regular retinotopic organization.(13) Moreover, there is evidence that retinotopic biases are carried forward into higher order visual areas.”
Qubad, M., Barnes-Scheufler, C. V., Schaum, M., Raspor, E., Rösler, L., Peters, B., Schiweck, C., Goebel, R., Reif, A., & Bittner, R. A. (2022) · Scientific Reports · doi:10.1038/s41598-022-17909-2 · Cited by 3
Functional Organization of the Primary Visual Cortex
Goebel, R. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00224-4 · Cited by 3
An extension of the studyforrest dataset for vision researchPreprint
Sengupta, A., Kaule, F. R., Guntupalli, J. S., Hoffmann, M. B., Häusler, C. O., Stadler, J., & Hanke, M. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/046573 · Cited by 3
Aberrant Visual Population Receptive Fields in Human AlbinismPreprint
Duwell, E. J., Woertz, E. N., Mathis, J., Carroll, J., & DeYoe, E. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/572289 · Cited by 3
Visual working memory representations in visual and parietal cortex do not remap after eye movementsPreprint
He, T., Ekman, M., Vandenbroucke, A. R. E., & de Lange, F. P. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/747329 · Cited by 3
“263 Retinotopic mapping of early visual areas (V1 – V3) 264 Early visual areas (V1, V2, and V3) for each participant were identified using two 265 retinotopic mapping blocks based on the standard traveling-wave method using 266 rotating wedges (DeYoe et al., 1996; Engel et al., 1997; Wandell et al., 2007), 267 consist…”
MethodRibeiro, F. L., Bollmann, S., & Puckett, A. M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.11.934471 · Cited by 4
Naturalistic Audiovisual Stimulation Reveals the Tonotopic Organization of Human Auditory CortexPreprint
Hedger, N., & Knapen, T. H. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.05.447566 · Cited by 3
“In analogy to the auditory brain, many visual brain regions are organized retinotopically: according to the structure of their sensory organ, the retina 9,10 .”
Neural Correlates of High-Level Visual Saliency ModelsPreprint
Kroner, A., Senden, M., & Goebel, R. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.29.551075 · Cited by 3
Chandra, S., Khona, M., Konkle, T., & Fiete, I. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.07.574543 · Cited by 5
“Areas in the early visual cortex such as V1, V2, V3, V4, and some areas in the lateral occipital cortex preserve the global topography of visual inputs to the retina [ 1, 2, 3, 4, 5, 6, 7 ] .”
BackgroundMethodInfluentialHuman V4 size predicts crowding distancePreprint
Kurzawski, J. W., Qiu, B. S., Majaj, N. J., Benson, N. C., Pelli, D. G., & Winawer, J. A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.03.587977 · Cited by 3
Visual working memories are abstractions of perceptsPreprint
Duan, Z., & Curtis, C. E. (2024) · eLife · doi:10.7554/elife.94191.2 · Cited by 3
Connectome of a human foveal retinaPreprint
Kim, Y. J., PACKER, O. S., Macrina, T., Pollreisz, A., Curcio, C. A., Lee, K., Kemnitz, N., Ih, D., Nguyen, T., Lu, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.05.647403 · Cited by 3
Eysel, U. T. (2019) · Springer-Lehrbuch · doi:10.1007/978-3-662-56468-4_59 · Cited by 2
Fregni, S., Wolfensteller, U., & Ruge, H. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf123 · Cited by 3
Metadata
- Authors
- Wandell, B. A., Dumoulin, S. O., & Brewer, A. A.
- Affiliations
- Stanford University (US)
- University of California, Irvine (US)
- Corresponding author
- Wandell, Brian A.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2007-10
- Volume
- 56
- Issue
- 2
- Pages
- 366-383
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2141073321
- Cited by
- 1,231
- References
- 179
- Citations by year
- 2026: 73 · 2025: 83 · 2024: 66 · 2023: 65 · 2022: 75 · 2021: 97 · 2020: 58 · 2019: 80 · 2018: 62 · 2017: 60 · 2016: 67 · 2015: 56 · 2014: 68 · 2013: 79 · 2012: 60
- FWCI
- 2.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 2152 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Larry L. Hillblom Foundation
- National Eye Institute (RO1 EY03164)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- visual field maps, receptive fields, human visual cortex, lateral occipital cortex, posterior parietal cortex, functional MRI, visual system organization
- MeSH terms
- Animals, Brain Mapping, Humans, Magnetic Resonance Imaging, Models, Anatomic, Models, Neurological, Visual Cortex, Visual Fields
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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